Ingest
Turn every document, archive, and internal site into searchable, source-linked knowledge.
Ingest a decade of circulars and procedures. Ask a question. Get page-numbered answers.
Your AI. Your governance.
Enterprise AI deployed where your data already lives. On-premise, air-gapped, or in your own cloud.
Currently in private preview with selected financial institutions across EMEA, with additional regulated-industry deployments under discussion.
One platform. Your infrastructure. Every regulated team.
deeplinq is the AI layer for enterprises that can't send their data to a vendor's cloud. We deploy inside your environment, connect to your legacy systems, and put governed agents in every team's hands — without a data science team.
What deeplinq does
Five things. Done well. On your infrastructure.
Connect
Read from and write to the systems your business already runs on — no rip-and-replace.
Query SAP, update Salesforce, trigger a core-banking workflow — from a single conversation.
Orchestrate
Run every leading LLM behind one governed layer. Switch models as your needs evolve.
Anthropic for legal summaries. Mistral on-prem for conversations. Your model for risk scoring.
Deploy
Ship AI agents scoped to a team, a use case, a compliance context — in days, not quarters.
An onboarding agent for retail banking. A circular-research agent for compliance. Each with its own guardrails.
Govern
Every prompt logged. Every answer traceable. Every access role-bound.
A full audit trail exportable for regulators. Role-based access controls. Topic guardrails enforced by policy.
What it changes
Hours back. Risk down. Control kept.
Regulated teams spend most of their week finding information, reconciling across systems, and producing paperwork. deeplinq lets them spend it on judgment.
Relationship Managers
From four systems to brief a client to one conversation that assembles the client view.
Compliance Officers
From reading 200 pages for one regulator question to a sourced answer with circular references in seconds.
Back-office Operations
From hours of manual reconciliation to agents that draft, check, and route for approval.
Executives
From waiting for the quarterly dashboard to asking the business a question and getting the answer today.
Outcomes based on design-partner pilots currently underway. Published case studies available as partners authorize disclosure.
Why deeplinq exists
From enterprise search to enterprise AI agents
2011
Brams, Google GSA enterprise partner, EMEA
2015
Bridge, contextual business views across indexed data (direct ancestor of deeplinq)
2023
deeplinq spun off as independent AI middleware
deeplinq began in 2011, when an EMEA team joined Google's Enterprise Search Appliance partners. Gulf deployments exposed the limits of rigid search — and the Bridge module that emerged is the direct ancestor of deeplinq. In 2023, deeplinq spun off as AI middleware for regulated enterprises.
deeplinq's team draws on fifteen years of enterprise data expertise, with three years of dedicated focus on enterprise AI middleware — engineered for the sovereign AI era.
Built for the teams that carry the risk
Every regulated team builds an agent of their own.
One platform. Team-scoped deployments. Your team defines the workflow; deeplinq provides connectors, orchestration, and audit trail. No shared context between agents unless authorized.
Relationship Managers
Client 360 data plane from the systems you already run. Meeting prep in seconds.
Compliance Officers
Regulatory research across circulars. Control-check workflows your team defines. Sourced answers.
Risk & Audit
Infrastructure for signal-detection workflows. Full audit trail on every decision.
Operations & Back-office
Reporting, reconciliation, document processing — drafted by agents, validated by your team.
Executives
Ask the business in natural language. Answers grounded in live data.
Developers & IT
Open APIs. MCP and A2A. Your models behind our orchestration. No lock-in.
No model lock-in
Use the best model for the job. Today, tomorrow, and when the frontier moves again.
deeplinq runs against the model that fits your sovereignty and compliance posture. Cloud APIs for non-sensitive workloads. Open-weights models for on-premise or air-gapped deployments. Switch per use case, per team, or per policy. When a better model ships, you get to adopt it. Not us.
Model-agnostic architecture means your organization routes tasks to the right model depending on sensitivity, performance, cost, and regulatory constraints — without locking your AI strategy into a single provider. When the frontier moves, you adopt. Your strategy doesn't depend on a vendor's roadmap.
Supported models
Cloud APIs (with data residency)
- OpenAI
- Anthropic
- Mistral
Open-weights (self-hosted)
- Llama
- Qwen
- Mistral open
- Gemma
- Falcon
Including your own fine-tuned or on-premise models. Additional providers on request.
Open protocols
- MCP (Model Context Protocol)
- Google A2A
- REST
- SSE
- WebSocket
Deployed where you need it
Four ways to run deeplinq. All inside your environment.
On-premise
Install on your own servers. Full control over hardware, networking, data.
For: institutions with mature infrastructure and strict residency.
Air-gapped
Zero outbound network dependency. For environments where telemetry is too much.
For: classified workloads, offline industrial environments.
Your own cloud
Deploy into AWS, Azure, Google Cloud, or sovereign cloud. You own infrastructure, we provide platform.
For: cloud-committed enterprises with data-residency control.
Managed SaaS
Multi-tenant deeplinq. EU-hosted by default. No data leaves the region you select.
For: innovation teams, proofs of concept, non-regulated workloads.
No proprietary hardware. No vendor lock-in.
deeplinq installs on your specified infrastructure — we adapt to what you have.
Deployment journey
12 weeks, 4 phases, co-constructed. From customer-side preparation to in-production operations, every phase is mapped — including the prerequisites on your side.
The architectural stance
Compliance by Design
Compliance is not a feature we bolt on. It is the architectural starting point.
Every platform component — audit core, access control, model routing, deployment topology — was built to satisfy regulated-industry evidence requirements. Our audit subsystem captures what no general-purpose framework provides: AI-specific evidence trails that document model version, decision context, human reviewer, and guardrail outcome for every consequential action.
Architected for alignment with universal frameworks. Regional adaptation reviewed on engagement for every deployment.
Built for regulated environments
Your data never leaves your jurisdiction.
Post-Schrems II, "EU region" ≠ "EU sovereignty". Regulators tighten, boards ask harder questions, AI vendors still ship prompts through infrastructure they don't fully control. deeplinq is engineered against the regulatory envelope your jurisdiction enforces — by region and by vertical.
Aligned by region and by vertical
Architecture aligned across the framework families that matter for regulated institutions.
Europe
GDPR, EU AI Act, DORA, MiFID II — architecture aligned, evidence layer ready.
Middle East & Africa
PDPL, Loi 09-08, regional data-protection regimes — residency by deployment location.
Banking
Operational resilience, decision traceability, regulator-ready exports for DPO and audit.
Public sector
Sovereign-cloud postures, data classification, citizen-residency-by-default.
Healthcare
GxP-class evidence, Annex 11 / HIPAA postures, patient-data perimeter preserved.
deeplinq runs inside your environment. Prompts, documents, connections, inference stay where your legal team said. No exfiltration by design. Not by policy. By architecture.
EU-grade data residency
Deployments respect jurisdiction. EU stays EU. UK stays UK. DACH stays DACH.
EU AI Act ready
Architected around EU AI Act transparency, logging, and risk-classification. Audit-ready from day one.
No third-party transmission
Queries never reach a vendor's cloud. Model calls on-premise. Your data is yours, end to end.
Beyond banking
The platform starts with banking. It doesn't stop there.
Our first engagements are in banking because that is where sovereignty, compliance, and legacy complexity are hardest. What works in a bank works in an insurer, an industrial operator, a public institution — with their own constraints and their own data that cannot move.
We are building deeplinq into the category platform for enterprise AI that runs inside the network edge — across regulated industries, across regions, with our partner ecosystem. One platform. Every regulated team. Your infrastructure.
Start a conversation. Not a sales process.
deeplinq is currently working with a small number of design partners across regulated industries in EMEA. If you're responsible for AI strategy, data governance, or a regulated workflow in a financial institution, pharma, public sector, telecom operator, insurer, utility, or regulated industrial — we'd like to hear from you.
25-minute conversation. No deck. We want to understand your constraints first.